In heavy-duty Battery Electric Commercial Vehicles, developing multi-speed transmissions with smaller traction motors is crucial for achieving necessary gradeability and improving operational efficiency. However, understanding the shifting process in electric vehicles, which lack physical clutches to disengage the transmission from the traction motor during gear shifts, presents a unique challenge. Traditional methods for estimating shift forces are not applicable, creating a new challenge for the industry. The rise of electric vehicles offers opportunities to optimize various aspects of mechanical powertrains, particularly through designing compact shift systems with smaller actuators for automated gear shifting. During gear shifts, the goal is to optimize the required shift force to match the load capacity of a smaller actuator, as failure to do so may result in unsuccessful shifts.
This paper evaluates and proposes a methodology for estimating the required shift force in an automated multi-speed transmission for an electric vehicle. By formulating a mathematical transfer function, the worst-case scenario resulting in the highest resistance from the base box is analyzed. The validity of this methodology is confirmed through quantitative vehicle-level testing on existing transmissions, showing an estimated shift force of 685.37 N with an error of 1.452%. The variables with the highest sensitivity are investigated. Latin Hypercube sampling is used to optimize these sensitive variables. The study aims to enhance shift quality, which depends on both the shift force and the time taken to complete a shift, ultimately leading to increased efficiency and driver comfort.